Mapgraph

Abstract

Online Analytical Processing is a database paradigm that provides for the rich analysis of multi-dimensional data. OLAP is often supported by a logical structure known as the Cube. However, supporting efficient OLAP query resolution in enterprise scale environments is an issue of considerable complexity. In practice, the difficulty of the problem is exacerbated by the existence of dimension hierarchies that sub-divide core dimensions into aggregation layers of varying granularity. Common hierarchy-sensitive query operations such as Rollup and Drilldown can be very costly on large cubes. Moreover, facilities for the representation of more complex hierarchical relationships are not well supported by conventional techniques. This paper presents a robust hierarchy infrastructure called mapGraph that supports the efficient and transparent manipulation of attribute hierarchies within OLAP environments. Experimental results verify that, when compared to the alternatives, very little additional overhead is introduced, even when advanced functionality is exploited.